Medical image enhancement in health care applications using modified sun flower optimization

Image enhancement (IE) is a process which improves the contrast of image by sharpening the edge pixels intensity. This technique has attained much attention in medical field and several enhancement techniques are proposed by researchers. In image processing, the enhancement is regarded as complex optimization issues. This work introduces an efficient model to solve optimization issues using a modified optimization approach. Initially, the input medical images are denoised using Modified median filter (MMF) filter. Then these denoised images are enhanced for the further process. The enhancement is carried out by pixel intensity of image. The parameters like entropy, edge information and intensity are optimized by modified sun flower optimization (MSFO). This optimization is used for increasing the convergence speed. The overall evaluation is carried in Matlab platform. The image quality is analyzed on six performance metrics and compared over several approaches and provided better results. The experimentation is evaluated on five medical images and the Mean square error (MSE) and peak signal noise ratio (PSNR) achieved by the medical image 1 are 0.02 and 43.7 respectively.